The prefrontal cortex is believed to be responsible for execution of deceptive behavior and its involvement is associated with greater cognitive efforts. It is also generally assumed that deception is associated with the inhibition of default honest actions. However, the precise neurophysiological mechanisms underlying this process remain largely unknown. The present study was aimed to use functional magnetic resonance imaging to reveal the underlying functional integration within the prefrontal cortex during the task which requires that subjects to deliberately mislead an opponent through the sequential execution of deceptive and honest claims. To address this issue, we performed psychophysiological interaction (PPI) analysis, which allows for statistical assessment of changes in functional relationships between active brain areas in changing psychological contexts. As a result the whole brain PPI-analysis established that both manipulative honest and deceptive claiming were associated with an increase in connectivity between the left middle frontal gyrus and right temporo-parietal junction (rTPJ). Taking into account the role played by rTPJ in processes associated with the theory of mind the revealed data can reflect possible influence of socio-cognitive context on the process of selecting manipulative claiming regardless their honest or deceptive nature. Direct comparison between deceptive and honest claims revealed pattern enhancement of coupling between the left middle frontal gyrus and the left inferior frontal gyrus. This finding provided evidence that the execution of deception relies to a greater extent on higher-order hierarchically-organized brain mechanisms of executive control required to select between two competing deceptive or honest task sets.

Functional connectivity between brain areas involved in the processing of complex language forms remains largely unexplored. Contributing to the debate about neural mechanisms underlying regular and irregular inflectional morphology processing in the mental lexicon, we conducted an fMRI experiment in which participants generated forms from different types of Russian verbs and nouns as well as from nonce stimuli. The data were subjected to a whole brain voxel-wise analysis of context dependent changes in functional connectivity (the so-called psychophysiological interaction analysis, PPI). Unlike previously reported subtractive results that reveal functional segregation between brain areas, PPI provides complementary information showing how these areas are functionally integrated in a particular task. To date, PPI evidence on inflectional morphology has been scarce and only available for inflectionally impoverished English verbs in a same-different judgment task. Using PPI here in conjunction with a production task in an inflectionally rich language, we found that functional connectivity between the left inferior frontal gyrus (LIFG) and bilateral superior temporal gyri (STG) was significantly greater for regular real verbs than for irregular ones. Furthermore, we observed a significant positive covariance between the number of mistakes in irregular real verb trials and the increase in functional connectivity between the LIFG and the right anterior cingulate cortex in these trails, as compared to regular ones. Our results therefore allow for dissociation between regularity and processing difficulty effects. These results, on the one hand, shed new light on the functional interplay within the LIFG-bilateral STG language-related network and, on the other hand, call for partial reconsideration of some of the previous findings while stressing the role of functional temporo-frontal connectivity in complex morphological processes.

Deception is a form of manipulation aimed at misleading another person by conveying false or truthful messages. Manipulative truthful statements could be considered as sophisticated deception and elicit an increased cognitive load. However, only one fMRI study reported its neural correlates. To provide independent evidence for sophisticated deception, we carried out an fMRI study replicating the experimental paradigm and Bayesian statistical approach utilized in that study. During the experiment, participants played a game against an opponent by sending deliberate deceptive or honest messages. Compared to truth-telling, deceptive intentions, regardless of how they were fulfilled, were associated with increased BOLD signals in the bilateral temporoparietal junction (TPJ), left precuneus, and right superior temporal sulcus (STS). The right TPJ participates in the attribution of mental states, acting in a social context, and moral behaviour. Moreover, the other revealed brain areas have been considered nodes in the theory of mind brain neural system. Therefore, the obtained results reflect an increased demand for socio‑cognitive processes associated with deceptive intentions. We replicated the original study showing the involvement of the right TPJ and expanded upon it by revealing the involvement of the left TPJ, left precuneus and right STS in actions with deceptive intentions.

Classical null hypothesis significance testing is limited to the rejection of the point-null hypothesis; it does not allow the interpretation of non-significant results. This leads to a bias against the null hypothesis. Herein, we discuss statistical approaches to ‘null effect’ assessment focusing on the Bayesian parameter inference (BPI). Although Bayesian methods have been theoretically elaborated and implemented in common neuroimaging software packages, they are not widely used for ‘null effect’ assessment. BPI considers the posterior probability of finding the effect within or outside the region of practical equivalence to the null value. It can be used to find both ‘activated/deactivated’ and ‘not activated’ voxels or to indicate that the obtained data are not sufficient using a single decision rule. It also allows to evaluate the data as the sample size increases and decide to stop the experiment if the obtained data are sufficient to make a confident inference. To demonstrate the advantages of using BPI for fMRI data group analysis, we compare it with classical null hypothesis significance testing on empirical data. We also use simulated data to show how BPI performs under different effect sizes, noise levels, noise distributions and sample sizes. Finally, we consider the problem of defining the region of practical equivalence for BPI and discuss possible applications of BPI in fMRI studies. To facilitate ‘null effect’ assessment for fMRI practitioners, we provide Statistical Parametric Mapping 12 based toolbox for Bayesian inference.